Remove useless bboxes&labels in CocoDataset

[ShiquanYu]

不好意思，PR #158 测试不周，，，，valid set 返回 NoneType 时会在collate时引发类型错误，修复了下这个问题～

[ShiquanYu]

以下是我对模型做了少量更改（为了部署）后得测试结果。

版本：commit 2021.2.22

修改内容：

1. leaky_relu -> relu6
2. PAN -> FPN
3. FPN(bilinear) -> FPN(nearest)

测试结果：
BGR：

mAP: 0.27045186089989737
AP_50: 0.4214516444114105
AP_75: 0.2862484957541031
AP_small: 0.10793292324828849
AP_m: 0.2944064369754226
AP_l: 0.39395007400120235

RGB：

mAP: 0.2794905872668077
AP_50: 0.4308761059392766
AP_75: 0.2924213184092761
AP_small: 0.11358375294212335
AP_m: 0.2997194595821626
AP_l: 0.4088541954988801

[stiansel]

Pardon, but why would you want to remove all images without bounding boxes? Isn't it beneficial for the model to learn not to produce boxes for these images? Does it cause an issue somewhere later in the training loop?

[ShiquanYu]

Pardon, but why would you want to remove all images without bounding boxes? Isn't it beneficial for the model to learn not to produce boxes for these images? Does it cause an issue somewhere later in the training loop?

It will only delete images without bboxes in valid set, and will not affect train set.

[stiansel]

Pardon, but why would you want to remove all images without bounding boxes? Isn't it beneficial for the model to learn not to produce boxes for these images? Does it cause an issue somewhere later in the training loop?

It will only delete images without bboxes in valid set, and will not affect train set.

I was thinking of these added lines in get_train_data:

        # Remove image without label&bbox
        if self.mode == 'train' and len(meta['gt_bboxes']) == 0:
            return None